activity
20242026
most citedMe LLaMA: Foundation Large Language Models for Medical Applications

8 citations · 14 across the 31 of their papers we have counts for

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17 papers · 1 filter

cs.CL2026

Factorized Hypothesis Search for Evidence-to-Taxonomy Retrieval

Linhai Ma, Ethan F. Wei, Xueqing Peng +3

Large-taxonomy retrieval often assumes that the input already expresses the target concept. In many settings, however, the input is indirect evidence, such as a table cell whose me…

cs.CL2026

Overview of FinMMEval 2026 Task 2: Multilingual Financial Short-Answer Question Answering

Zhuohan Xie, Xueqing Peng, Georgi Georgiev +18

FinMMEval 2026 Task 2 evaluates short-answer financial question answering over multilingual evidence. Each final-test item pairs an English question with financial statements and n…

cs.CL2026

Overview of FinMMEval 2026 Task 1: Multilingual Financial Multiple-Choice Question Answering

Zhuohan Xie, Yuyang Dai, Rania Elbadry +18

FinMMEval 2026 Task 1 evaluates multilingual financial multiple-choice question answering in English, Chinese, Arabic, and Hindi. The task tests whether systems can select the corr…

cs.CL2026

The CLEF-2026 FinMMEval Lab: Multilingual and Multimodal Evaluation of Financial AI Systems

Zhuohan Xie, Rania Elbadry, Fan Zhang +12

We present the setup and the tasks of the FinMMEval Lab at CLEF 2026, which introduces the first multilingual and multimodal evaluation framework for financial Large Language Model…

cs.CL2026

Ebisu: Benchmarking Large Language Models in Japanese Finance

Xueqing Peng, Ruoyu Xiang, Fan Zhang +9

Japanese finance combines agglutinative, head-final linguistic structure, mixed writing systems, and high-context communication norms that rely on indirect expression and implicit…

cs.CL2026

EHRNavigator: A Multi-Agent System for Patient-Level Clinical Question Answering over Heterogeneous Electronic Health Records

Lingfei Qian, Mauro Giuffre, Yan Wang +11

Clinical decision-making increasingly relies on timely and context-aware access to patient information within Electronic Health Records (EHRs), yet most existing natural language q…